About Rattle
Rattle (the R Analytical Tool To Learn Easily) is an open-source graphical user interface (GUI) for data science and machine learning in R.
Rattle, which stands for the R Analytical Tool To Learn Easily, is an open-source Graphical User Interface (GUI) for performing data science and data mining tasks using the R programming language. Developed by Togaware, it is designed to make the power of R accessible to a broader audience, including those who are not expert programmers. The tool allows users to explore data through statistical and visual summaries, transform datasets for modeling, and build both unsupervised and supervised machine learning models. A key feature is its ability to generate the underlying R code for every action performed in the GUI, serving as an excellent learning tool. Rattle is a free, downloadable package available on CRAN and is used in both academic and commercial settings. It runs on Windows, MacOS, and GNU/Linux. As it is open-source software, there are no published pricing plans or formal support tiers.
Pros & Cons
- Open-source and free to use, available on CRAN.
- Provides a graphical user interface, making R's data mining capabilities more accessible.
- Automatically generates R code, which is a great learning tool for users new to R.
- Supports a wide range of data science tasks from data exploration to model building and evaluation.
- Available for Windows, MacOS, and GNU/Linux operating systems.
- As an open-source project, it lacks dedicated commercial support options like live chat or phone support.
- The website does not provide a centralized list of features, requiring users to infer capabilities from documentation and blog posts.
Features
Key features
Provides a point-and-click graphical interface powered by Flutter and R, making machine learning and data mining accessible without manual coding.
Captures every user GUI interaction and outputs the corresponding underlying R script for learning, reproducible research, and batch execution.
Builds, evaluates, and compares both supervised and unsupervised models, including decision trees, random forests, neural networks, and clustering algorithms.
Presents statistical summaries, visual profiling, data distributions, and transformations natively designed to prepare datasets for modeling.
Evaluates performance using built-in ROC curves, risk charts, and confusion matrices while providing scoring capabilities for new datasets.
Additional features
Provides a point-and-click graphical interface powered by Flutter and R, making machine learning and data mining accessible without manual coding.
Captures every user GUI interaction and outputs the corresponding underlying R script for learning, reproducible research, and batch execution.
Builds, evaluates, and compares both supervised and unsupervised models, including decision trees, random forests, neural networks, and clustering algorithms.
Presents statistical summaries, visual profiling, data distributions, and transformations natively designed to prepare datasets for modeling.
Evaluates performance using built-in ROC curves, risk charts, and confusion matrices while providing scoring capabilities for new datasets.
Operates across GNU/Linux, macOS, and Microsoft Windows environments.
Features an open-source front-end hosted on GitHub and R support packages on Bitbucket for custom contributions and extensions.
Includes subsetted real-world datasets, such as weatherAUS, for immediate hands-on training and practice.
Pricing
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About Rattle
Rattle (the R Analytical Tool To Learn Easily) is an open-source graphical user interface (GUI) for data science and machine learning in R.
Rattle Details
Rattle's In-App Market Place
Does Rattle have an in-app market place?
Yes
How many Mini-Apps in the marketplace?
0
Mini Apps
Pricing Options
Accepted Payment Currencies
USD
Pros & Cons
- Open-source and free to use, available on CRAN.
- Provides a graphical user interface, making R's data mining capabilities more accessible.
- Automatically generates R code, which is a great learning tool for users new to R.
- Supports a wide range of data science tasks from data exploration to model building and evaluation.
- Available for Windows, MacOS, and GNU/Linux operating systems.
- As an open-source project, it lacks dedicated commercial support options like live chat or phone support.
- The website does not provide a centralized list of features, requiring users to infer capabilities from documentation and blog posts.
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